Integrative Analyses and Verification of the Expression and Prognostic Significance for RCN1 in Glioblastoma Multiforme

Glioblastoma multiform is a lethal primary brain tumor derived from astrocytic, with a poor prognosis in adults. Reticulocalbin-1 (RCN1) is a calcium-binding protein, dysregulation of which contributes to tumorigenesis and progression in various cancers. The present study aimed to identify the impact of RCN1 on the outcomes of patients with Glioblastoma multiforme (GBM). The study applied two public databases to require RNA sequencing data of Glioblastoma multiform samples with clinical data for the construction of a training set and a validation set, respectively. We used bioinformatic analyses to determine that RCN1 could be an independent factor for the overall survival of Glioblastoma multiform patients. In the training set, the study constructed a predictive prognostic model based on the combination of RCN1 with various clinical parameters for overall survival at 0.5-, 1.0-, and 1.5-years, as well as developed a nomogram, which was further validated by validation set. Pathways analyses indicated that RCN1 was involved in KEAS and MYC pathways and apoptosis. In vitro experiments indicated that RCN1 promoted cell invasion of Glioblastoma multiform cells. These results illustrated the prognostic role of RCN1 for overall survival in Glioblastoma multiform patients, indicated the promotion of RCN1 in cell invasion, and suggested the probability of RCN1 as a potential targeted molecule for treatment in Glioblastoma multiform.

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Heme Biosynthesis mRNA Expression Signature: Towards a Novel Prognostic Biomarker in Patients with Diffusely Infiltrating Gliomas

Cancers ◽

10.3390/cancers13040662 ◽

2021 ◽

Vol 13 (4) ◽

pp. 662

Author(s):

Mario Mischkulnig ◽

Barbara Kiesel ◽

Daniela Lötsch ◽

Thomas Roetzer ◽

Martin Borkovec ◽

...

Keyword(s):

Overall Survival ◽

Mrna Expression ◽

Postoperative Management ◽

Heme Biosynthesis ◽

The Cancer Genome Atlas ◽

Sequencing Data ◽

Who Grade ◽

Expression Signature ◽

Cancer Genome Atlas ◽

The Impact

Diffusely infiltrating gliomas are characterized by a variable clinical course, and thus novel prognostic biomarkers are needed. The heme biosynthesis cycle constitutes a fundamental metabolic pathway and might play a crucial role in glioma biology. The aim of this study was thus to investigate the role of the heme biosynthesis mRNA expression signature on prognosis in a large glioma patient cohort. Glioma patients with available sequencing data on heme biosynthesis expression were retrieved from The Cancer Genome Atlas (TCGA). In each patient, the heme biosynthesis mRNA expression signature was calculated and categorized into low, medium, and high expression subgroups. Differences in progression-free and overall survival between these subgroups were investigated including a multivariate analysis correcting for WHO grade, tumor subtype, and patient age and sex. In a total of 693 patients, progression-free and overall survival showed a strictly monotonical decrease with increasing mRNA expression signature subgroups. In detail, median overall survival was 134.2 months in the low, 79.9 months in the intermediate, and 16.5 months in the high mRNA expression signature subgroups, respectively. The impact of mRNA expression signature on progression-free and overall survival was independent of the other analyzed prognostic factors. Our data indicate that the heme biosynthesis mRNA expression signature might serve as an additional novel prognostic marker in patients with diffusely infiltrating gliomas to optimize postoperative management.

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High numbers of tumor-infiltrating FOXP3-positive regulatory T cells are associated with improved overall survival in follicular lymphoma

Blood ◽

10.1182/blood-2006-04-018218 ◽

2006 ◽

Vol 108 (9) ◽

pp. 2957-2964 ◽

Cited By ~ 342

Author(s):

Joaquim Carreras ◽

Armando Lopez-Guillermo ◽

Bridget C. Fox ◽

Lluis Colomo ◽

Antonio Martinez ◽

...

Keyword(s):

Overall Survival ◽

T Cells ◽

Regulatory T Cells ◽

Follicular Lymphoma ◽

International Prognostic Index ◽

Prognostic Significance ◽

Prognostic Index ◽

Specific Cell ◽

First Relapse ◽

The Impact

Abstract The tumor microenvironment plays an important role in the biologic behavior of follicular lymphoma (FL), but the specific cell subsets involved in this regulation are unknown. To determine the impact of FOXP3-positive regulatory T cells (Tregs) in the progression and outcome of FL patients, we examined samples from 97 patients at diagnosis and 37 at first relapse with an anti-FOXP3 monoclonal antibody. Tregs were quantified using computerized image analysis. The median overall survival (OS) of the series was 9.9 years, and the FL International Prognostic Index (FLIPI) was prognostically significant. The median Treg percentage at diagnosis was 10.5%. Overall, 49 patients had more than 10% Tregs, 30 between 5% to 10%, and 19 less than 5%, with a 5-year OS of 80%, 74%, and 50%, respectively (P = .001). Patients with very low numbers of Tregs (< 5%) presented more frequently with refractory disease (P = .007). The prognostic significance of Treg numbers was independent of the FLIPI. Seven transformed diffuse large B-cell lymphomas (DLBCLs) had lower Treg percentages (mean: 3.3%) than FL grades 1,2 (mean: 12.1%) or 3 (mean: 9%) (P < .02). In conclusion, high Treg numbers predict improved survival of FL patients, while a marked reduction in Tregs is observed on transformation to DLBCL.

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Low expression of MN1 associates with better treatment response in older patients with de novo cytogenetically normal acute myeloid leukemia

Blood ◽

10.1182/blood-2011-06-357764 ◽

2011 ◽

Vol 118 (15) ◽

pp. 4188-4198 ◽

Cited By ~ 40

Author(s):

Sebastian Schwind ◽

Guido Marcucci ◽

Jessica Kohlschmidt ◽

Michael D. Radmacher ◽

Krzysztof Mrózek ◽

...

Keyword(s):

Overall Survival ◽

Acute Myeloid Leukemia ◽

Older Patients ◽

Myeloid Leukemia ◽

Hox Genes ◽

De Novo ◽

Prognostic Significance ◽

The Impact ◽

Favorable Group ◽

Acute Myeloid

AbstractLow MN1 expression bestows favorable prognosis in younger adults with cytogenetically normal acute myeloid leukemia (CN-AML), but its prognostic significance in older patients is unknown. We analyzed pretherapy MN1 expression in 140 older (≥ 60 years) de novo CN-AML patients treated on cytarabine/daunorubicin-based protocols. Low MN1 expressers had higher complete remission (CR) rates (P = .001), and longer overall survival (P = .03) and event-free survival (EFS; P = .004). In multivariable models, low MN1 expression was associated with better CR rates and EFS. The impact of MN1 expression on overall survival and EFS was predominantly in patients 70 years of age or older, with low MN1 expressers with mutated NPM1 having the best outcome. The impact of MN1 expression was also observed in the Intermediate-I, but not the Favorable group of the European LeukemiaNet classification, where low MN1 expressers had CR rates and EFS similar to those of Favorable group patients. MN1 expresser-status-associated gene- and microRNA-expression signatures revealed underexpression of drug resistance and adverse outcome predictors, and overexpression of HOX genes and HOX-gene–embedded microRNAs in low MN1 expressers. We conclude that low MN1 expression confers better prognosis in older CN-AML patients and may refine the European LeukemiaNet classification. Biologic features associated with MN1 expression may help identify new treatment targets.

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Prognostic Significance of the Combined Expression of Matrix Metalloproteinase-9, Urokinase Type Plasminogen Activator and its Receptor in Breast Cancer as Measured by Northern Blot Analysis

The International Journal of Biological Markers ◽

10.1177/172460080101600109 ◽

2001 ◽

Vol 16 (1) ◽

pp. 62-68 ◽

Cited By ~ 19

Author(s):

M.M. Pacheco ◽

I.N. Nishimoto ◽

M. Mourão Neto ◽

E.B. Mantovani ◽

M.M. Brentani

Keyword(s):

Breast Cancer ◽

Overall Survival ◽

Plasminogen Activator ◽

Northern Blot ◽

Blot Analysis ◽

Northern Blot Analysis ◽

Prognostic Significance ◽

Mrna Levels ◽

Upa Mrna ◽

The Impact

Using Northern blot analysis we have measured the co-expression of the matrix metalloprotease MMP-9, plasminogen activator urokinase type (uPA) and its receptor (uPAR) mRNAs in 81 biopsies of breast carcinomas with the objective of analyzing the impact of these factors on the overall survival probability of the patients (median follow-up time: 4 years). Individual mRNA levels of either uPA or uPAR showed parallel variations with MMP-9 mRNA, suggesting a coordinate transcription of these markers. When median values were used as cutoff points to discriminate between high and low factor expression, no association was found with patient outcome and MMP-9 or uPA mRNA distribution. However, increased uPAR mRNA levels were associated with poor prognosis (p = 0.01). The combination of MMP-9 and uPAR mRNA measurements has not enhanced prognostic information compared to information supplied by the receptor alone (p = 0.01). The combination of MMP-9 and high levels of uPA mRNA led to a significant association with poor outcome (p = 0.03). Multivariate analysis supported the notion that increased uPAR mRNA production in primary breast cancer may be a predictor of overall survival.

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ASXL1 Mutations in AML: Molecular Biomarker for Secondary AML?

Blood ◽

10.1182/blood.v124.21.2343.2343 ◽

2014 ◽

Vol 124 (21) ◽

pp. 2343-2343

Author(s):

Jingmei Hsu ◽

Anita J. Kumar ◽

Martin P. Carroll ◽

Noelle V. Frey ◽

Nirav N. Shah ◽

...

Keyword(s):

Overall Survival ◽

De Novo ◽

Conflicts Of Interest ◽

Prognostic Significance ◽

Myeloproliferative Neoplasm ◽

Molecular Characteristics ◽

Intermediate Risk ◽

Kaplan Meier ◽

The Impact

Abstract Background: Additional sex combs like transcription factor 1 (ASXL1) is a member of the polycomb group protein. ASXL1 mutation has been implicated in myeloid malignancy transformation. It is hypothesized that mutated ASXL1 leads to the loss of polycomb repressive complex 2 (PRC2) mediated gene repression and subsequent transforming events. Recent studies identify ASXL1 mutation as a poor prognostic marker in patients (pts) with de novo acute myeloid leukemia (AML) who present with intermediate–risk cytogenetic lesions (Patel, NEJM 2012; Schnittger, Leukemia2013). To study the impact of ASXL1 mutations in an unselected AML population, we analyzed clinical and molecular characteristics of patients with untreated AML who express ASXL1 mutation at presentation. Methods: Using next generation sequencing, 254 adult patients with AML seen at the Hospital of the University of Pennsylvania were analyzed for mutations, including ASXL1, using a 33-gene hematologic malignancy panel. Clinical characteristics were obtained from retrospective chart review. Kaplan-Meier estimates were used to calculate overall survival (OS) from time of diagnosis. Living patients were censored at date last seen. Results: ASXL1 mutations were detected in 36/254 (14%) AML pts. There were 29 known pathologic mutations, 1 benign, 1 probable pathologic, and 9 variants of unknown clinical significance (VUS). In 6/36 (16.7%) pts, ASXL1 was the sole mutation identified. Of the 30 pts with additional mutations (Figure 1), 6/30 (20%) pts harbored 2 independent ASXL1 mutations. When the 27 patients with pathologic ASCL mutations were analyzed for co-mutations, TET2 (13/27, 48%) was the most frequent ASXL1 co-mutation. FLT3 (0/27, 0%) and NPM1 (1/27, 3.7%) were notable for their absence. Median age of pts at diagnosis was 69 years (range 23-80). Prior myelodysplastic syndrome (MDS) or myeloproliferative neoplasm (MPN) was noted in 9/36 (25%) and 11/36 (30.6%) pts, respectively. Four pts (11.1%) had received chemotherapy and/or radiation therapy for a prior non-myeloid neoplasm. Karyotype was normal in 18/36 (50%) pts, and 7 additional pts had intermediate cytogenetic lesions. There were 7 pts (19.4%) with unfavorable cytogenetics (complex karyotype (3 pts), 7q- (3 pts), and 5q- (1 pt)). Four pts (11.1%) had a favorable karyotype, with t(8;21) in 3 pts and t(15;17) in 1 pt. At presentation, median white blood cell count (WBC) was 6.4x103/uL (1.0 x -103). In pts whose AML transformed from prior MPN, median WBC was 50 X103/uL (3.3-140). Standard induction chemotherapy with an anthracycline and cytarabine was given to 17/36 (47%) pts. An additional 3/36 (8.3%) pts underwent induction therapy with clofarabine. Complete remission (CR) was documented in 14/20 (70%) evaluable pts. Of the remaining pts, 11 received a hypomethylating agent, and 5 received other therapies. Thirty-day treatment mortality for all 36 pts and for 27 pts with known ASXL1 pathologic mutation was 13.4% and 18.5% respectively. Kaplan-Meier estimate showed a median overall survival of 349 days (median follow up of 107 days (range 15-1570)). For the 27 pts with a pathologic ASXL1 mutation, the OS was 276 days (Figure 2, median follow up of 145 days (range 18-1570)). Conclusion: ASXL1 mutations in de novo AML with intermediate-risk cytogenetics is associated with poor clinical outcome in cooperative group trials. Strikingly we demonstrate in a single institution, retrospective analysis that 66.7% of pts who present with ASXL1 mutations in the setting of previously untreated AML had documented MDS, MPN and/or prior chemotherapy/radiation. Further studies are necessary to evaluate if ASXL1 mutation has independent prognostic significance in AML or if it is primarily a marker for secondary leukemia. Figure 1: ASXL1 and co-mutations Figure 1:. ASXL1 and co-mutations Figure 2: Overall survival for AML patients with ASXL1 pathologic mutation Figure 2:. Overall survival for AML patients with ASXL1 pathologic mutation Disclosures No relevant conflicts of interest to declare.

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Risk Stratification Model for Predicting the Overall Survival of Elderly Triple-Negative Breast Cancer Patients: A Population-Based Study

Frontiers in Medicine ◽

10.3389/fmed.2021.705515 ◽

2021 ◽

Vol 8 ◽

Author(s):

Xiaozhu Liu ◽

Song Yue ◽

Haodong Huang ◽

Minjie Duan ◽

Binyi Zhao ◽

...

Keyword(s):

Breast Cancer ◽

Overall Survival ◽

Risk Stratification ◽

Elderly Patients ◽

Triple Negative ◽

Training Set ◽

Medium Risk ◽

Validation Set ◽

Stratification System ◽

Risk Stratification System

Background: The objective of this study was to evaluate the prognostic value of clinical characteristics in elderly patients with triple-negative breast cancer (TNBC).Methods: The cohort was selected from the Surveillance, Epidemiology, and End Results (SEER) program dating from 2010 to 2015. Univariate and multivariate analyses were performed using a Cox proportional risk regression model, and a nomogram was constructed to predict the 1-, 3-, and 5-year prognoses of elderly patients with TNBC. A concordance index (C-index), calibration curve, and decision curve analysis (DCA) were used to verify the nomogram.Results: The results of the study identified a total of 5,677 patients who were randomly divided 6:4 into a training set (n = 3,422) and a validation set (n = 2,255). The multivariate analysis showed that age, race, grade, TN stage, chemotherapy status, radiotherapy status, and tumor size at diagnosis were independent factors affecting the prognosis of elderly patients with TNBC. Together, the 1 -, 3 -, and 5-year nomograms were made up of 8 variables. For the verification of these results, the C-index of the training set and validation set were 0.757 (95% CI 0.743–0.772) and 0.750 (95% CI 0.742–0.768), respectively. The calibration curve also showed that the actual observation of overall survival (OS) was in good agreement with the prediction of the nomograms. Additionally, the DCA showed that the nomogram had good clinical application value. According to the score of each patient, the risk stratification system of elderly patients with TNBC was further established by perfectly dividing these patients into three groups, namely, low risk, medium risk, and high risk, in all queues. In addition, the results showed that radiotherapy could improve prognosis in the low-risk group (P = 0.00056), but had no significant effect in the medium-risk (P < 0.4) and high-risk groups (P < 0.71). An online web app was built based on the proposed nomogram for convenient clinical use.Conclusion: This study was the first to construct a nomogram and risk stratification system for elderly patients with TNBC. The well-established nomogram and the important findings from our study could guide follow-up management strategies for elderly patients with TNBC and help clinicians improve individual treatment.

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Overall Survival in Patients with JAK2 and ASXL1 Positive Myeloproliferative Neoplasms

Blood ◽

10.1182/blood-2019-128309 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 5383-5383

Author(s):

Murtadha Al-Khabori ◽

Shoaib Al-Zadjali ◽

Iman Al Noumani ◽

Khalil Al Farsi ◽

Salam Al-Kindi ◽

...

Keyword(s):

Overall Survival ◽

Board Of Directors ◽

Myeloproliferative Neoplasms ◽

Prognostic Significance ◽

Jak2 V617f ◽

World Health ◽

Prognostic Impact ◽

Advisory Committees ◽

Myeloid Neoplasms ◽

The Impact

Objectives: Mutations in additional sex combs-like transcriptional regulator 1 (ASXL1) have been previously described in myeloid neoplasms (21% in non-Myeloproliferative [MPN; Tefferi A, Leukemia, 2010) and have been associated with a more aggressive disease [Rocquain J et al, BMC Cacer, 2010]. They can also be found in patients with JAK2 positive MPN [Abdel-Wahab O et al, Cancer Research, 2010). Disruption of ASXL1 gene leads to MPN phenotype in zebrafish model (Gjini E, Dis Model Mech, 2019). The co-expression and the prognostic significance of ASXL1 in patients with JAK2 positive MPN are not yet fully defined. We therefore planned to define the prognostic impact of ASXL1 mutations on the Overall Survival (OS) of patients with JAK2 positive MPN. Methods: We included patients with JAK2 V617F positive MPN diagnosed according to the World Health Organization 2016 criteria and treated at the three largest hematology centers in Oman. The entire coding region of ASXL1 gene was sequenced using Next Generation Sequencing (NGS; Ion PGM Sequencer; Thermo Fisher Scientific®). The library was constructed and the templates were prepared using the PGM tool and the variants were annotated using the ClinVar database and the prediction from the Scale-Invariant Feature Transform (SIFT) and or Polymorphism Phenotyping (Polyphen) algorithms. The NGS analysis was done on the frozen diagnostic bone marrow samples. The survival probability was estimated using Kaplan-Meier estimator and Cox regression was used to assess the impact of predictors on the OS outcome. An alpha threshold of 0.05 was used. The R program (version 3.1.2) was used for all statistical analyses. Results: A total of 58 patients with JAK2 V617F positive MPN were included. All of these patients were found to have mutated ASXL1 using the NGS (ASXL1 p.Leu815Pro was found in all patients). The median age of this cohort was 62 years (InterQuartile Range [IQR]: 44 - 70) and female to male ratio was 25:33. The median hemoglobin, hematocrit, white blood cell count and platelet count was 14.7 g/dL, 58%, 11.5 x109/L and 518 x109/L respectively. Out of the 58 patients included, 28 had polycythemia vera, 20 had essential thrombocythemia, 8 had myelofibrosis and 2 had MPN-Unclassified. The median time from diagnosis to last follow up or death was 13 months (IQR: 3-39). During this period, 5 patients died. The probability of OS at 3 years was 88%. The median OS was not reached. In the univariable analysis, age was a statistically significant predictor of OS (p = 0.0355) but not gender (p = 0.434) and MPN subtype (p = 0.7). In the multivariable analysis model of the previous three factors, age remained statistically significant (Hazard ratio = 1.13, p = 0.041). Conclusions: ASXL1 is mutated in high proportion of patients with JAK2 positive MPN. Despite the negative impact of ASXL1 in patients with non-MPN myeloid neoplasms, the patients with combined positivity of JAK2 and ASXL1 in this study had a very good OS probability. Age was a predictor of OS in the univariable and multivariable models. We recommend the development and the assessment of ASXL1 inhibitors as therapeutic strategies in patients with MPN. Disclosures Al-Khabori: Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; NovoNardisk: Membership on an entity's Board of Directors or advisory committees; Servier: Membership on an entity's Board of Directors or advisory committees; Shire (Takeda): Membership on an entity's Board of Directors or advisory committees; SOBI: Honoraria; AstraZeneca: Honoraria; Abbvie: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees.

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A nomogram based on pretreatment CT radiomics features for predicting complete response to chemoradiotherapy in patients with esophageal squamous cell cancer

10.21203/rs.3.rs-41188/v2 ◽

2020 ◽

Author(s):

Hesan Luo ◽

Shao-Fu Huang ◽

Hong-Yao Xu ◽

Xu-Yuan Li ◽

Sheng-Xi Wu ◽

...

Keyword(s):

Logistic Regression ◽

Squamous Cell ◽

Cell Cancer ◽

Complete Response ◽

Clinical Staging ◽

Training Set ◽

Simple Method ◽

Validation Set ◽

The Impact ◽

Radiomics Signature

Abstract Purpose: To develop and validate a nomogram model to predict complete response (CR) after concurrent chemoradiotherapy (CCRT) in esophageal squamous cell carcinoma (ESCC) patients using pretreatment CT radiomic features. Methods: Data of patients diagnosed as ESCC and treated with CCRT in Shantou Central Hospital during the period from January 2013 to December 2015 were retrospectively collected. Eligible patients were included in this study and randomize divided into a training set and a validation set after successive screening. The least absolute shrinkage and selection operator (LASSO) with logistic regression to select radiomics features calculating Rad-score in the training set. The logistic regression analysis was performed to identify the predictive clinical factors for developing a nomogram model. The area under the receiver operating characteristic curves (AUC) was used to assess the performance of the predictive nomogram model and decision curve was used to analyze the impact of the nomogram model on clinical treatment decisions. Results: A total of 226 patients were included and randomly divided into two groups, 160 patients in training set and 66 patients in validation set. After LASSO analysis, seven radiomics features were screened out to develop a radiomics signature Rad-score. The AUC of Rad-score was 0.812 (95%CI: 0.742-0.869, p<0.001) in the training set and 0.744 (95%CI: 0.632-0.851, p=0.003) in the validation set. Multivariate analysis showed that Rad-score and clinical staging were independent predictors of CR status, with P values of 0.035 and 0.023, respectively. A nomogram model incorporating Rad-socre and clinical staging was developed and validated, with an AUC of 0.844 (95％CI: 0.779-0.897) in the training set and 0.807 (95％CI: 0.691-0.894) in the validation set．Delong test showed that the nomogram model was significantly superior to the clinical staging, with P<0.001 in the training set and P=0.026 in the validation set. The decision curve showed that the nomogram model was superior to the clinical staging when the risk threshold was greater than 25%. Conclusion: We developed and validated a nomogram model for predicting CR status of ESCC patients after CCRT. The nomogram model was combined radiomics signature Rad-score and clinical staging. This model provided us with an economical and simple method for evaluating the response of chemoradiotherapy for patients with ESCC.

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Predicting outcome in patients with moderate to severe traumatic brain injury using electroencephalography

Critical Care ◽

10.1186/s13054-019-2656-6 ◽

2019 ◽

Vol 23 (1) ◽

Cited By ~ 4

Author(s):

Marjolein E. Haveman ◽

Michel J. A. M. Van Putten ◽

Harold W. Hom ◽

Carin J. Eertman-Meyer ◽

Albertus Beishuizen ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Random Forest ◽

Outcome Prediction ◽

Training Set ◽

Arterial Blood ◽

Continuous Eeg ◽

Severe Tbi ◽

Validation Set ◽

The Impact

Abstract Background Better outcome prediction could assist in reliable quantification and classification of traumatic brain injury (TBI) severity to support clinical decision-making. We developed a multifactorial model combining quantitative electroencephalography (qEEG) measurements and clinically relevant parameters as proof of concept for outcome prediction of patients with moderate to severe TBI. Methods Continuous EEG measurements were performed during the first 7 days of ICU admission. Patient outcome at 12 months was dichotomized based on the Extended Glasgow Outcome Score (GOSE) as poor (GOSE 1–2) or good (GOSE 3–8). Twenty-three qEEG features were extracted. Prediction models were created using a Random Forest classifier based on qEEG features, age, and mean arterial blood pressure (MAP) at 24, 48, 72, and 96 h after TBI and combinations of two time intervals. After optimization of the models, we added parameters from the International Mission for Prognosis And Clinical Trial Design (IMPACT) predictor, existing of clinical, CT, and laboratory parameters at admission. Furthermore, we compared our best models to the online IMPACT predictor. Results Fifty-seven patients with moderate to severe TBI were included and divided into a training set (n = 38) and a validation set (n = 19). Our best model included eight qEEG parameters and MAP at 72 and 96 h after TBI, age, and nine other IMPACT parameters. This model had high predictive ability for poor outcome on both the training set using leave-one-out (area under the receiver operating characteristic curve (AUC) = 0.94, specificity 100%, sensitivity 75%) and validation set (AUC = 0.81, specificity 75%, sensitivity 100%). The IMPACT predictor independently predicted both groups with an AUC of 0.74 (specificity 81%, sensitivity 65%) and 0.84 (sensitivity 88%, specificity 73%), respectively. Conclusions Our study shows the potential of multifactorial Random Forest models using qEEG parameters to predict outcome in patients with moderate to severe TBI.

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Importance of Achieving a Complete Response in Multiple Myeloma, and the Impact of Novel Agents

Journal of Clinical Oncology ◽

10.1200/jco.2009.25.4250 ◽

2010 ◽

Vol 28 (15) ◽

pp. 2612-2624 ◽

Cited By ~ 153

Author(s):

Asher A. Chanan-Khan ◽

Sergio Giralt

Keyword(s):

Multiple Myeloma ◽

Overall Survival ◽

Prognostic Significance ◽

Complete Response ◽

Maximal Response ◽

Prognostic Impact ◽

Long Term Outcomes ◽

First Line ◽

The Impact

The goal of treatment for multiple myeloma (MM) is to improve patients' long-term outcomes. One important factor that has been associated with prolonged progression-free and overall survival is the quality of response to treatment, particularly achievement of a complete response (CR). There is extensive evidence from clinical studies in the transplant setting in first-line MM demonstrating that CR or maximal response post-transplant is significantly associated with prolonged progression-free and overall survival, with some studies demonstrating a similar association with postinduction response. Supportive evidence is also available from studies in the nontransplant and relapsed settings. With the introduction of bortezomib, thalidomide, and lenalidomide, higher rates of CR are being achieved in both first-line and relapsed MM compared with previous chemotherapeutic approaches, thereby potentially improving long-term outcomes. While standard CR by established response criteria has been shown to have differential prognostic impact compared with lesser responses, increasingly sensitive analytic techniques are now being explored to define more stringent degrees of CR or elimination of minimal residual disease (MRD), including multiparameter flow cytometry and polymerase chain reaction. Demonstrating eradication of MRD by these techniques has already been shown to predict for improved outcomes. Here, we review the prognostic significance of achieving CR in MM and highlight the importance of CR as an increasingly realizable goal at all stages of treatment. We discuss clinical management issues and provide recommendations relevant to practicing oncologists, such as the routine use of sensitive techniques for assessment of disease status to inform evidence-based decisions on optimal patient management.

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